Objective
The course gives a comprehensive introduction to machine learning,
which is a field concerned with learning from examples and has
roots in computer science, statistics and pattern recognition. The
objective is realized by presenting methods and tools proven
valuable and by addressing specific application problems.
The program is based on a combination of academic, problem-oriented and interdisciplinary approaches and organized based on the following work and evaluation methods that combine skills and reflection:
Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student
Name of exam | Machine Learning |
Type of exam | Written or oral exam |
ECTS | 5 |
Assessment | Passed/Not Passed |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Elective course
On this semester two courses must be chosen out of three elective
courses (total: 10 ECTS).
Danish title | Maskinlæring |
Module code | N-IRS-K3-3 |
Module type | Course |
Duration | 1 semester |
Semester | Autumn
|
ECTS | 5 |
Language of instruction | English |
Empty-place Scheme | Yes |
Location of the lecture | Campus Esbjerg |
Responsible for the module |
Study Board | Study Board of Build, Energy, Electronics and Mechanics in Esbjerg |
Department | Department of Energy |
Faculty | The Faculty of Engineering and Science |